Detections
Explore public detection logic contributed by the community across SIEM and rule languages.
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This rule detects kernel crash signatures (e.g., use-after-free, kernel panic) in the pppoe module, correlated with preceding anomalous activity related to PPPoEject or PPPoE socket manipulation. It identifies potential exploitation of CVE-2026-68121 on non-gateway devices.
Detects a suspected exploitation attempt of CVE-2026-81000, known as TUNderflow. The detection looks for a sequence of events where a process initializes a user namespace (unshare) followed by a kernel panic or error report from the tun/tap driver originating from the same process lineage within a short timeframe, which is indicative of an integer overflow exploit leading to kernel instability.
This rule detects kernel-level stability issues or crashes (ah6/ipsec related) occurring immediately after the execution of processes that create new user namespaces (unshare, clone with CLONE_NEWUSER). This pattern is often associated with exploitation of kernel vulnerabilities, where namespace manipulation is a prerequisite for triggering a crash or privilege escalation.
This rule detects a high volume of SCTP traffic targeted at internal systems, characterized by mass endpoint creation. This behavior is indicative of an exploit attempt against the 'sctp_diag' kernel component (CVE-2026-74469), which can lead to an out-of-bounds (OOB) write condition, potentially resulting in system instability or denial of service.
This rule detects the execution of specific suspicious filenames (dirtyah6, tunderflow, pppoeject, diagspill) when they are launched from common staging or temporary directories such as /tmp, /home, or /root, while excluding known build environments, package management directories, and common development workspaces.
Detects a large volume of file write, rename, or creation operations within a single minute by a single process, concurrently with the creation of files containing common ransomware keywords (e.g., 'readme', 'decrypt', 'how_to'). This behavior is characteristic of ransomware encryption activities.
This rule monitors command-line activity for common scripting interpreters (Python, PowerShell, Bash, CMD) and flags processes that contain suspicious commentary. It looks for excessive use of comments (3 or more) or specific narrative phrases often found in malicious scripts, such as references to encrypting, dropping, deleting, or escalating privileges, which are indicative of obfuscated or malicious intent.
This rule detects a sequence of suspicious events related to the 'ENCFORGE' threat actor or toolset. It monitors for evidence of initial access (via validation/code API calls), command and control communication (to specific IP/port), and destructive impact, correlating these activities within a 4-hour window on the same host.
Detects suspicious Python execution patterns commonly associated with web shells or remote code execution, originating from typical web server or application middleware processes (e.g., w3wp, nginx, httpd, tomcat). The detection triggers on specific patterns including base64-encoded command execution, Python evaluation of base64-encoded strings, or long alphanumeric command-line strings suggesting obfuscated code execution.
Detects Python scripts that exhibit behavioral characteristics of agentic or LLM-generated malicious code. This is identified by the presence of self-narrating comments describing intent, next steps, or staging/exfiltration actions, combined with hardcoded indicators for the JADEPUFFER staging infrastructure.
Detects high-frequency execution of Python interpreter processes within a short timeframe (40+ distinct command lines in 15 minutes). This behavioral pattern is indicative of automated or autonomous agent-driven payload delivery and execution, as seen in JADEPUFFER and ENCFORGE campaigns.
This rule detects attempts to exploit Apache Nacos vulnerabilities, including authentication bypass and unauthorized administrative account creation. It monitors process executions of common tools (like curl and java) and network connections targeting known Nacos service ports (8848, 9848) containing indicators of exploit patterns such as login bypass endpoints or SQL injection sequences targeting the user table.
Detects the presence of natural-language self-narration in code comments within Python or SQL scripts. This pattern is indicative of LLM-driven agentic execution, where automated agents narrate their own malicious actions, such as enumeration, data exfiltration, or database manipulation, as observed in the JADEPUFFER campaign.
Detects the execution of MySQL process command lines that simultaneously contain the strings 'AES_ENCRYPT' and 'UPDATE'. This pattern often indicates attempts to manipulate data within the database via SQL injection or unauthorized database modification.
Detects potential SQL injection attempts by monitoring for 'INSERT INTO' SQL commands executed via command-line arguments. The rule specifically looks for operations targeting user or role tables and including administrative keywords, originating from database or application-related processes like mysql or java.
Detects the ENCFORGE locker malware, associated with the JADEPUFFER campaign, which specifically targets AI/ML-related files such as model checkpoints, vector databases, and training data for the purpose of malicious encryption or destruction.
Detects attempts to delete, truncate, or overwrite critical system logs and user command history files (such as /var/log/auth.log, syslog, or .bash_history) on Linux systems using common utilities like rm, shred, and truncate. The rule includes exclusions for legitimate system maintenance processes like logrotate and cron.
Detects the use of the 'tar' utility with the '--use-compress-program' flag, where the compression program specified is not a standard system compression tool. This pattern is commonly used by attackers to execute arbitrary payloads when tar extracts malicious archives.
Detects administrator-privileged actions in JFrog Artifactory audit logs attributed to the 'token:anonymous' identity, the tell-tale signature left when CVE-2026-42018 (unauthenticated token retrieval) is chained with CVE-2026-42016 (privilege escalation) to mint an admin-scope token that retains the anonymous username. Also relevant to CVE-2026-82329 authentication bypass activity.
Detects malicious shell commands attempting to perform supply-chain persistence via environment variable manipulation in CI/CD environments. The rule identifies processes injecting BASH_ENV into GITHUB_ENV, a known technique used by the SCKIT supply-chain worm to perform credential harvesting during CI pipeline execution.
Detects malicious shell commands attempting to perform supply-chain persistence via environment variable manipulation in CI/CD environments. The rule identifies processes injecting BASH_ENV into GITHUB_ENV, a known technique used by the SCKIT supply-chain worm to perform credential harvesting during CI pipeline execution.
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